Back
Mid-level AI role in a metro with popular title but niche MCP integrations reduces applicant density.
Skills are transferable across enterprises but require domain-specific MCP, governance, and cloud integration experience.
Explicit 5-8 years, mandatory tech stack and domain-specific MCP/enterprise integration requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead the design, deployment, and operationalization of MCP-based AI integration tools connecting LLMs with enterprise apps, APIs, and data.
Build and maintain integrations across Azure, ServiceNow, Databricks, Microsoft 365, Jira, and other line-of-business applications.
Define standards and develop reusable frameworks for tool discovery, access control, authentication, governance, observability, and performance optimization.
5-8+ years work experience in AI engineering or related field.
Strong hands-on experience with MCP, Python, TypeScript, REST APIs, OAuth, Azure, Kubernetes, and enterprise AI integration architecture.
Experience with API gateways, enterprise security, DevOps, and observability tools.
Location requirement: Mumbai, India.
Senior engineer capable of leading enterprise-wide AI tool deployment and integration.
Experienced in collaborating with AI architects and business teams to productionize AI use cases.
Familiar with multi-tenant MCP architectures and enterprise governance frameworks.